How is HPC Shifting From On-premises Environments to the Cloud

How You Use HPC Today

HPC is ideally used to compute complex math problems. Such examples include:

• Computational Fluid Dynamics: Engineers can scale-out Computational Fluid Dynamics simulation jobs to experiment with more tunable parameters, leading to faster, more accurate results.
• Genomics: HPC provides the inherent scalability and an ecosystem of tools for running genomics workloads.
• Reservoir Simulation: HPC delivers the flexibility to support unique CPU and GPU configurations, scale, and elasticity to support spiky optimization workflows, like automated history-matching.
• Risk Management & Portfolio Optimization: HPC offers portfolio managers to quickly conduct simulations that identify risks within a given portfolio of products, hedging opportunities, and areas for optimization.
• Autonomous Vehicles - Driving Simulation: HPC provides a full suite of services to support Autonomous Vehicle development and deployment.
• Research Computing and Higher Education: HPC helps researchers process complex workloads by providing secure compute, storage and database capabilities needed to accelerate time-to-science.

As can be seen, there are many scenarios where HPC centers have been of value.

Bringing HPC to the Cloud

In many ways, HPC is a precursor to a private Cloud environment. With an HPC, you have an extensive battery of servers set up to run problems with a specific configuration of the server environment. In many ways, this is no different to a Cloud environment. To this end, Cloud hosting companies such as AWS, Microsoft Azure, and Google Cloud now all offer HPC solutions.

The advantage that a Cloud hosting provider can offer for HPC customers comes in two formats:

• Scale and Elasticity: the services can scale up and down to meet the needs of the customer.
• Services: a Cloud provider offers a slew of services that can be adapted and used for data collected from the HPC.

A typical Cloud setup for an HPC cluster is to use the same servers used in the Cloud itself. Each of the leading Cloud providers offers solutions at a much larger scale and demand than any HPC center. Also, a Cloud provider can apply its economies of scale to an HPC configuration to offer engineers flexible configuration setups that can be powered up instantly versus waiting for new server hardware to arrive.

Cloud hosting companies such as AWS are making the jump from HPC to Cloud easier. AWS delivers integrated services that provide everything needed to quickly build and manage HPC clusters in the Cloud to run the most compute-intensive workloads across various industry verticals. 

HPC on AWS removes the long wait times and lost productivity often associated with on-premises HPC clusters. Flexible configuration and almost unlimited scalability allow you to flex your infrastructure to match your workloads instead of throttling workloads based on infrastructure. Because AWS gives you access to a suite of cloud-based services like Data Analytics, Artificial Intelligence (AI), and Machine Learning (ML), you can innovate faster by redefining traditional HPC workflows.

In many ways, the biggest gain of moving an HPC to the Cloud is cost. With HPC on a cloud service provider, you avoid the upfront capital expenditures and protracted procurement cycles of an on-premises implementation. You pay only for the capacity you use, and flexible pricing models offer significant cost savings when you process time-flexible, stateless workloads. Where an on-premises HPC runs the risk of becoming obsolete as technology changes or becoming underutilized as workloads change, HPC in the Cloud gives you access to new technologies as they are introduced without requiring you to replace hardware. The result is more efficient HPC spending with fewer wasted resources.

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The Future of HPC

In many ways, the future of HPC is already here: it's the Cloud. Cloud providers offer more services, higher resilience, and more efficient scalability than any HPC center can offer. 

However, there may still be an argument for using an on-premises HPC for organizations or applications that require privacy. In such cases, there are two additional options. The first is a Private Cloud. The Private Cloud solution is again hosted in a cloud data center but with an extra layer of security to isolate the content from the Public Cloud. The second is a hybrid cloud where the core data crunching takes place in a traditional HPC, but low-risk services and functions are outsourced to a Cloud provider. The second option is often used by companies who are concerned about the risk of moving to the Private Cloud option.

In many ways, companies choosing Hybrid Cloud are just stalling until they see the need to move to the full Cloud (either public or private). The rapid advancement of AI, services, and ways to program directly in the Cloud via Functions offers too many positive reasons to abandon an HPC and move straight to the Cloud.

If you need additional skills to participate in the future of HPC in the Cloud, consider Simplilearn's courses in AWS, Azure, and Google Cloud technology, or the Simplilearn Cloud Architect Master's Program that covers all three Cloud platforms.  To become more proficient with the tools that manage HPC operations, you may wish to pursue Simplilearn's courses in DevOps or the comprehensive DevOps Engineer Master's Program.